Tower
Tower Software Labs · Productivity · AI Assistant
Tower is an AI due diligence platform for M&A, legal, and real estate deals. It organizes data rooms, answers questions across documents, and tracks review work in one workspace.
About Tower
What Is Tower
Tower is a diligence workspace rather than another chat window bolted onto a data room. You hand it a request list and a messy set of files. It renames the files, indexes each record against the list, and tells you what's still missing. The team then reviews, flags issues, and generates deliverables inside the same place. For a firm comparing AI due diligence software, that single system is the whole argument.
That packaging targets the part of a deal that eats the calendar. Collecting and verifying disclosures usually runs across several virtual data rooms, an Excel tracker, and a long email thread. Tower pulls those into one system per deal, so buy side, sell side, lenders, and outside counsel all work from the same record.
The limits are worth knowing before you book a call. Tower sells through demos, with no self-serve signup and no published price list, so you'll need a conversation to find out what it costs. It also expects real deal volume to pay off. A solo practitioner handling one transaction a year will get less out of it than a serial acquirer running several at once.
Getting Started
- Book a demo with the Tower team, since there's no free trial or self-serve plan to poke at on your own.
- Create a workspace for the deal and upload files or sync an existing data room into it.
- Load your diligence request list, then let Tower rename, index, and gap check the incoming records.
- Invite the deal team and outside parties, assigning each group its own permissions and owners.
- Ask questions across the full document set, then export reports, disclosure schedules, or memoranda for review.
Product Information
A quick look at Tower's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Transactional lawyers
- Corporate development teams
- Commercial real estate acquisitions teams
- Buy side advisors and lenders
Tasks
- Cleaning up a messy data room
- Answering questions across thousands of documents
- Tracking diligence requests
- Drafting disclosure schedules and DD reports
Scenarios
- A seller drops 400 files two weeks late
- A lease portfolio with hundreds of agreements
- Multi party deals with outside counsel
- Post close integration work
Key features
Data Room Organization on Upload
Tower takes files as they arrive, renames them to a convention you set, and indexes every record against the request list. Missing items get flagged in the same pass. The practical result is a room that's reviewable the day it opens instead of three weeks in.
One Workspace per Deal
Each asset or transaction gets its own space with owners, group permissions, notes, and live progress tracking. Buy side, sell side, lenders, and each advisor see only what they should. That separation matters in auctions, where showing a lender the buyer's internal notes is a real risk.
Document Q&A with Citations
You can ask a question across thousands of documents at once and get a structured answer back in a format you choose. Every answer carries verifiable citations, so a lawyer can jump to the clause rather than trust a summary. That citation trail is what makes the output usable in a deal file.
Issue Flagging as Files Land
Tower watches for the things you tell it to watch: expirations, missing pages, amendments, change of control terms. Flags fire when a file hits the room, not when someone eventually reads it. Catching a lapsed lease on day one changes what you ask for in the next request round.
Prebuilt Agents and Bring Your Own AI
Firms already invested in an AI tool can connect it to Tower and run it on deal data. Everyone else can use Tower's agents to generate DD reports, disclosure schedules, and memoranda. Saved prompts and playbooks keep a firm's own method in the loop instead of flattening every deal into one generic template.
Diligence Request Tracking
Requests, responses, and follow ups sit in one live system shared by every stakeholder. Tower drafts replies from documents already in the room and keeps a timestamped record of who asked what. For a lead counsel managing four workstreams, that's the difference between a status call and a status guess.
Document Analytics
The analytics view shows which parties opened a document, how long they spent, and what they returned to. Teams use it to pace a process and decide which follow ups to prioritize. It's a read on where the deal actually stands, not where the tracker says it stands.
Pros and cons
Pros
- Consolidates the data room, request tracker, and AI review tool into one workspace per deal, which removes the copy and paste step between systems.
- Citations on every AI answer let reviewers verify a claim in one click, a requirement for legal and financial work.
- Bring your own AI support means a firm doesn't have to abandon a model or vendor it already approved.
- Enterprise security posture is documented, including SOC 2 Type II, AES-256 encryption at rest, zero data retention with AI providers, and a choice of US or Canadian data hosting.
- Role based permissions extend to outside counsel and lenders, so multi party deals don't require a second room.
Cons
- No published pricing and no self-serve plan, so evaluating cost takes a sales conversation before you can compare it against alternatives.
- There's no free tier or trial, which makes it hard for a small firm to test the workflow on a live matter first.
- Setup depends on having a request list and folder conventions ready, so teams without a defined diligence process will need to build one.
- The value scales with deal volume. If you run one transaction a year, the per deal cost of onboarding may not pay back.
Frequently asked questions
Tower organizes a deal's documents, checks them against a diligence request list, flags what's missing, and lets the team query every file with cited AI answers. It also tracks requests and generates deliverables like disclosure schedules. Think of it as the workspace where collection, review, and output happen in one place.
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